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Which National Factors Are Most Influential in the Spread of COVID-19?

Author

Listed:
  • Hakyong Kim

    (Department of Industrial Engineering, Seoul National University, Seoul 08826, Korea
    These authors contributed equally to this work as co-first authors.)

  • Catherine Apio

    (Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, Korea
    These authors contributed equally to this work as co-first authors.)

  • Yeonghyeon Ko

    (Department of Statistics, Seoul National University, Seoul 08826, Korea
    Department of Archeology and Art History, Seoul National University, Seoul 08826, Korea
    These authors contributed equally to this work as co-first authors.)

  • Kyulhee Han

    (Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, Korea)

  • Taewan Goo

    (Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, Korea)

  • Gyujin Heo

    (Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, Korea)

  • Taehyun Kim

    (Department of Statistics, Seoul National University, Seoul 08826, Korea)

  • Hye Won Chung

    (Department of Chemistry, Seoul National University, Seoul 08826, Korea)

  • Doeun Lee

    (Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, Korea)

  • Jisun Lim

    (The Research Institute of Basic Sciences, Seoul National University, Seoul 08826, Korea)

  • Taesung Park

    (Department of Statistics, Seoul National University, Seoul 08826, Korea)

Abstract

The outbreak of the novel COVID-19, declared a global pandemic by WHO, is the most serious public health threat seen in terms of respiratory viruses since the 1918 H1N1 influenza pandemic. It is surprising that the total number of COVID-19 confirmed cases and the number of deaths has varied greatly across countries. Such great variations are caused by age population, health conditions, travel, economy, and environmental factors. Here, we investigated which national factors (life expectancy, aging index, human development index, percentage of malnourished people in the population, extreme poverty, economic ability, health policy, population, age distributions, etc.) influenced the spread of COVID-19 through systematic statistical analysis. First, we employed segmented growth curve models (GCMs) to model the cumulative confirmed cases for 134 countries from 1 January to 31 August 2020 (logistic and Gompertz). Thus, each country’s COVID-19 spread pattern was summarized into three growth-curve model parameters. Secondly, we investigated the relationship of selected 31 national factors (from KOSIS and Our World in Data ) to these GCM parameters. Our analysis showed that with time, the parameters were influenced by different factors; for example, the parameter related to the maximum number of predicted cumulative confirmed cases was greatly influenced by the total population size, as expected. The other parameter related to the rate of spread of COVID-19 was influenced by aging index, cardiovascular death rate, extreme poverty, median age, percentage of population aged 65 or 70 and older, and so forth. We hope that with their consideration of a country’s resources and population dynamics that our results will help in making informed decisions with the most impact against similar infectious diseases.

Suggested Citation

  • Hakyong Kim & Catherine Apio & Yeonghyeon Ko & Kyulhee Han & Taewan Goo & Gyujin Heo & Taehyun Kim & Hye Won Chung & Doeun Lee & Jisun Lim & Taesung Park, 2021. "Which National Factors Are Most Influential in the Spread of COVID-19?," IJERPH, MDPI, vol. 18(14), pages 1-22, July.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:14:p:7592-:d:595750
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    References listed on IDEAS

    as
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